Normalization

[1] 18112 1284

##Exploratory Analysis ### Library sizes

[1] 1284

[1] 2820424 73459397

[1] 23567225

### PCA plots

Density plot

#Density plot with all samples
# cpm table = ppmi_cpm_case_control
# log cpm table = lcpm

lcounts = log2(mynd_counts)
lcpm = log2(mynd_cpm)
ltpm = log2(mynd_abundance)
# voom use log already

nsamples <- ncol(mynd_cpm)
#samplenames <- colnames(mynd_cpm)

colfunc <- colorRampPalette(c("#4DBBD5FF", "#3C5488FF"))
col = alpha(colfunc(nsamples), alpha = 0.1)

#png(paste0(work_plots, "Density_all.#png"), width = 8, height = 6, res = 300, units = "in")
par(mfrow=c(2,2))
#COUNTS
plot(density(lcounts[,1]), col=col[1], lwd=2, ylim=c(0,0.26), las=2, main="", xlab="")
title(main="A. COUNTS ", xlab="Log2(counts)")
#abline(v=lcpm.cutoff, lty=3)
for (i in 2:nsamples){
  den <- density(lcounts[,i])
  lines(den$x, den$y, col=col[i], lwd=2)
}
#legend("right", samplenames, text.col=col, bty="n")

#CPM
plot(density(lcpm[,1]), col=col[1], lwd=2, ylim=c(0,0.26), las=2, main="", xlab="")
title(main="B. CPM ", xlab="Log2(CPM)")
#abline(v=lcpm.cutoff, lty=3)
for (i in 2:nsamples){
  den <- density(lcpm[,i])
  lines(den$x, den$y, col=col[i], lwd=2)
}
#legend("right", samplenames, text.col=col, bty="n")

#TPM
plot(density(ltpm[,1]), col=col[1], lwd=2, ylim=c(0,0.26), las=2, main="", xlab="")
title(main="C. TPM ", xlab="Log2(TPM)")
#abline(v=ltpm.cutoff, lty=3)
for (i in 2:nsamples){
  den <- density(ltpm[,i])
  lines(den$x, den$y, col=col[i], lwd=2)
}
#legend("right", samplenames, text.col=col, bty="n")

#Voom
plot(density(mynd_voom[,1]), col=col[1], lwd=2, ylim=c(0,0.26), las=2, main="", xlab="")
title(main="D. VOOM ", xlab="voom")
#abline(v=lvoom.cutoff, lty=3)
for (i in 2:nsamples){
  den <- density(mynd_voom[,i])
  lines(den$x, den$y, col=col[i], lwd=2)
}
#legend("right", samplenames, text.col=col, bty="n")
#dev.off()